DataKitchen

AUGUST 9, 2021

Instead of having a giant, unwieldy data lake , the data mesh breaks up the data and workflow assets into controllable and composable domains with inherent interdependencies. Domains are built from raw data and/or the output of other domains. We call this collection of capabilities observable meta-orchestration.

Testing 246

Testing Data Lake Metadata Publishing 246

AWS Big Data

AUGUST 3, 2023

Data analytics on operational data at near-real time is becoming a common need. Due to the exponential growth of data volume, it has become common practice to replace read replicas with data lakes to have better scalability and performance. For more information, see Changing the default settings for your data lake.

Data Lake 98

Data Lake Visualization Dashboards Insurance 98

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

Data Lake 59

Data Lake Data Warehouse Data Integration Management 59

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Run the following Shell script commands in the console to copy the Jupyter Notebooks.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Data Ingestion.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

AWS Big Data

APRIL 18, 2024

This is a guest blog post co-authored with Atul Khare and Bhupender Panwar from Salesforce. The Normalized Parquet Logs are stored in an Amazon Simple Storage Service (Amazon S3) data lake and cataloged into Hive Metastore (HMS) on an Amazon Relational Database Service (Amazon RDS) instance based on S3 event notifications.

Optimization 111

Optimization Data Lake Management Key Performance Indicator 111

Data Virtualization

MARCH 16, 2023

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

Data Lake 52

Data Lake Strategy Data Integration Enterprise 52

Data Virtualization

MARCH 16, 2023

Reading Time: 6 minutes Data lake, by combining the flexibility of object storage with the scalability and agility of cloud platforms, are becoming an increasingly popular choice as an enterprise data repository. Whether you are on Amazon Web Services (AWS) and leverage AWS S3.

Data Lake 52

Data Lake Strategy Data Integration Enterprise 52

Data Virtualization

NOVEMBER 3, 2022

Reading Time: 4 minutes The amount of expanding volume and variety of data originating from various sources are a massive challenge for businesses. In attempts to overcome their big data challenges, organizations are exploring data lakes as repositories where huge volumes and varieties of.

Data Lake 52

Data Lake Big Data Data Integration Management 52

Cloudera

JUNE 2, 2022

allowing developers to connect to any data source anywhere with any structure, process it, and deliver to any destination. This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? What is the modern data stack?

Enterprise 104

Enterprise Data Lake Data Collection Data-driven 104

Data Virtualization

OCTOBER 5, 2022

For this reason, organizations must periodically revisit their data architectures, to ensure that they are aligned with current business goals.

Data Lake 52

Data Lake Data Architecture Data Integration Management 52

AWS Big Data

NOVEMBER 6, 2023

Amazon EMR Studio is an integrated development environment (IDE) that makes it straightforward for data scientists and data engineers to develop, visualize, and debug data engineering and data science applications written in R, Python, Scala, and PySpark. This helps you reduce operational overhead.

Data Lake 111

Data Lake Sales Management Testing 111

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 94

Data Lake Data Warehouse Machine Learning Data-driven 94

CIO Business Intelligence

APRIL 25, 2022

Now generally available, the M&E data lakehouse comes with industry use-case specific features that the company calls accelerators, including real-time personalization, said Steve Sobel, the company’s global head of communications, in a blog post. Features focus on media and entertainment firms.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

DataKitchen

JANUARY 3, 2022

For example, teams working under the VP/Directors of Data Analytics may be tasked with accessing data, building databases, integrating data, and producing reports. Data scientists derive insights from data while business analysts work closely with and tend to the data needs of business units.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

CDW Research Hub

JULY 18, 2022

One modern data platform solution that provides simplicity and flexibility to grow is Snowflake’s data cloud and platform. These Snowflake accelerators reduce the time to analytics for your users at all levels so you can make data-driven decisions faster. Security Data Lake. Overall data architecture and strategy.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

Data Virtualization

JULY 1, 2021

If we look at a typical , many of its stages have more to do with data than science. Before data scientists can begin their work regarding data science, they often must begin by: Finding the right data Gaining access.

Data Science 52

Data Science Data Lake IT Data Warehouse 52

CIO Business Intelligence

JULY 13, 2022

allowing developers to connect to any data source anywhere with any structure, process it, and deliver to any destination. This blog aims to answer two questions: What is a universal data distribution service? Why does every organization need it when using a modern data stack? What is the modern data stack?

Enterprise 88

Enterprise Data Lake Data Collection Data-driven 88

AWS Big Data

AUGUST 19, 2024

Open the secret blog-glue-snowflake-credentials. For AWS Secret , choose the secret blog-glue-snowflake-credentials. For IAM Role , choose the role that has access to the target S3 location where the job is writing to and the source location from where it’s loading the Snowflake data and also to run the AWS Glue job.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

DataKitchen

JUNE 12, 2023

We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

Testing 130

Testing Dashboards Data Science Data Lake 130

Data Virtualization

APRIL 30, 2025

Modern data architectures like data lakehouses and cloud-native ecosystems were supposed to solve this, promising centralized access and scalability. The post Why Every Organization Needs a Data Marketplace appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Architecture 64

Data Architecture Data Integration Management IT 64

Alation

OCTOBER 7, 2021

In this essay, Jason reflects on the value of thinking spatially about data, showing how his experience as a graduate student influences his role as a data scientist today. The popularity of location data and GIS-styled analyses has amplified a common cry in GIS- turned-data-science circles: “Spatial isn’t special!”

Data Lake 98

Data Lake Visualization Data Science Digital Transformation 98

Cloudera

OCTOBER 11, 2021

Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x. Modak Nabu reliably curates datasets for any line of business and personas, from business analysts to data scientists. Customers using Modak Nabu with CDP today have deployed Data Lakes and.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Cloudera

DECEMBER 14, 2022

OCBC identified the need to upgrade its data lake technology as part of an enterprise data science initiative to introduce a more resilient infrastructure and platform capable of managing projects with increasing volume, variety and velocity of data, while also enabling real-time analytics. .

Data Strategy 81

Data Strategy Strategy IT Contextual Data 81

Cloudera

NOVEMBER 29, 2021

Carrefour Spain , a branch of the larger company (with 1,250 stores), processes over 3 million transactions every day, giving rise to challenges like creating and managing a data lake and honing down key demographic information. . Working with Cloudera, Carrefour Spain was able to create a unified data lake for ease of data handling.

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

Cloudera

NOVEMBER 18, 2020

To ensure maximum momentum and flawless service the Experian BIS Data Enrichment team decided to use the power of big data by utilizing Cloudera’s Data Science Workbench. This enabled Merck KGaA to control and maintain secure data access, and greatly increase business agility for multiple users.

Internet Publishing and Broadcasting 123

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 123

Cloudera

JULY 9, 2018

Some call it the “golden triangle,” but in this blog, we refer to it as the iron triangle. Most organizations struggle to unlock data science in the enterprise. It’s powerful features finally get data scientists, analysts, and business teams speaking the same language. Why the Data Science Iron Triangle Matters.

Machine Learning 42

Machine Learning Data Science Visualization Business Intelligence 42

Cloudera

AUGUST 18, 2021

Data processed at the edge or in the cloud, for instance, is not effective if it follows the traditional lifecycle of “ingest, process, land, and analyze.” If the data goes into a data lake before analysis, extracting it can get pretty complex and time-consuming.

Data Lake 88

Data Lake IoT Internet of Things Data-driven 88

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

Cloudera

JUNE 6, 2024

To keep pace as banking becomes increasingly digitized in Southeast Asia, OCBC was looking to utilize AI/ML to make more data-driven decisions to improve customer experience and mitigate risks. Learn more about how Cloudera helped OCBC unlock business value with trusted data.

Contextual Data 83

Contextual Data Data Lake Data-driven Risk 83

Cloudera

JANUARY 21, 2021

Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. The Data Lake service in Cloudera’s Data Platform provides a central place to understand, manage, secure, and govern data assets across the enterprise.

Data Warehouse 94

Data Warehouse Data Lake IT Analytics 94

Cloudera

DECEMBER 8, 2020

Federated Learning is a paradigm in which machine learning models are trained on decentralized data. Instead of collecting data on a single server or data lake, it remains in place — on smartphones, industrial sensing equipment, and other edge devices — and models are trained on-device.

Machine Learning 85

Machine Learning Data Lake Reporting Data Collection 85

Cloudera

JUNE 16, 2022

CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report. Without context, streaming data is useless.” ” SSB enables users to configure data providers using out of the box connectors or their own connector to any data source. Not in the manufacturing space?

Data Lake 88

Data Lake Manufacturing Metadata Dashboards 88

IBM Big Data Hub

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI.

Data Lake 77

Data Lake Metadata Data Warehouse Cost-Benefit 77

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” According to Gartner, Inc.

Metadata 102

Metadata Machine Learning Unstructured Data Data Lake 102